1. Field
This application relates to outlier correction. Outliers (or outlier values) are values in a signal which exceed a given tolerance lane with respect to a “normal” situation by far, i.e., which are outside the tolerance of the expected value of the signal. Such a signal may be represented as discrete series of values over time. For example, in a time series describing production figures of a production process in a supply chain management (SCM) application, a cause for outliers may be production interruption due to a natural disaster, or a production peak due to extraordinary advertising activities.
2. Background
In the art, there exists an algorithm for outlier correction in a historical time series based on an ex-post forecast algorithm. In this method, the outliers in an actual series of values are removed in order to get a series of values which represent the “normal” expected development of the process over time. This corrected series of (historical) values may then be used as a basis for a forecast of the process in the future.